Dear all,
I am trying to find a turning point in some data. In the initial phase, the
data increases more or less exponentially (thus it is linear in a nat log
transform), then reaches a plateau. I would like to find the point that
marks the end of the exponential phase.
I understand that the function spline can build a curve; is it possible
with it to find the turning points? I have no idea of how to use spline
though.
Here is a working example.
Thank you
```
Y = c(259, 716, 1404, 2173, 3944, 5403, 7140, 9121,
11220, 13809, 16634, 19869, 23753, 27447,
30590, 33975, 36627, 39600, 42067, 44082,
58190, 63280, 65921, 67929, 69977, 71865,
73614, 74005, 74894, 75717, 76365, 76579,
77087, 77493, 77926, 78253, 78680, 79253,
79455, 79580, 79699, 79838, 79981, 80080,
80124, 80164, 80183, 80207, 80222, 80230,
80241, 80261, 80261, 80277, 80290, 80303,
80337, 80376, 80422, 80461, 80539, 80586,
80653, 80708, 80762, 80807, 80807, 80886,
80922, 80957, 80988, 81007, 81037, 81076,
81108, 81108, 81171, 81213, 81259, 81358,
81466, 81555, 81601, 81647, 81673, 81998,
82025, 82041, 82053, 82064, 82094, 82104,
82110, 82122, 82133, 82136, 82142, 82164,
82168, 82180, 82181, 82184, 82187, 82188,
82190, 82192, 82193, 82194)
Y = log(Y)
X = 1:length(Y)
plot(Y ~ X, ylab = "Ln(Y)", xlim=c(0,10, main="zoomed in"))
abline(lm(Y[1:3] ~ X[1:3]))
abline(lm(Y[1:5] ~ X[1:5]), lty=2)
text(7, 6, "After third or fifth point, there is deviance", pos=3)
text(2.5, 10, "Solid line: linear model points 1:3", pos =3)
text(2.5, 9, "Dashed line: linear model points 1:5", pos =3)
plot(Y ~ X, ylab = "Ln(Y)", xlim=c(0,10, main="overall"))
abline(lm(Y[1:3] ~ X[1:3]))
```
How to find a split point in a curve?
5 messages · Luigi Marongiu, Rui Barradas, Bert Gunter +2 more
Hello, Are you looking for a segmented regression? fit <- lm(Y ~ X) seg <- segmented::segmented(fit, seg.Z = ~X) seg$psi[, 'Est.'] #[1] 29.21595 plot(X, Y) plot(seg, add = TRUE) Hope this helps, Rui Barradas ?s 16:12 de 14/05/20, Luigi Marongiu escreveu:
Dear all,
I am trying to find a turning point in some data. In the initial phase, the
data increases more or less exponentially (thus it is linear in a nat log
transform), then reaches a plateau. I would like to find the point that
marks the end of the exponential phase.
I understand that the function spline can build a curve; is it possible
with it to find the turning points? I have no idea of how to use spline
though.
Here is a working example.
Thank you
```
Y = c(259, 716, 1404, 2173, 3944, 5403, 7140, 9121,
11220, 13809, 16634, 19869, 23753, 27447,
30590, 33975, 36627, 39600, 42067, 44082,
58190, 63280, 65921, 67929, 69977, 71865,
73614, 74005, 74894, 75717, 76365, 76579,
77087, 77493, 77926, 78253, 78680, 79253,
79455, 79580, 79699, 79838, 79981, 80080,
80124, 80164, 80183, 80207, 80222, 80230,
80241, 80261, 80261, 80277, 80290, 80303,
80337, 80376, 80422, 80461, 80539, 80586,
80653, 80708, 80762, 80807, 80807, 80886,
80922, 80957, 80988, 81007, 81037, 81076,
81108, 81108, 81171, 81213, 81259, 81358,
81466, 81555, 81601, 81647, 81673, 81998,
82025, 82041, 82053, 82064, 82094, 82104,
82110, 82122, 82133, 82136, 82142, 82164,
82168, 82180, 82181, 82184, 82187, 82188,
82190, 82192, 82193, 82194)
Y = log(Y)
X = 1:length(Y)
plot(Y ~ X, ylab = "Ln(Y)", xlim=c(0,10, main="zoomed in"))
abline(lm(Y[1:3] ~ X[1:3]))
abline(lm(Y[1:5] ~ X[1:5]), lty=2)
text(7, 6, "After third or fifth point, there is deviance", pos=3)
text(2.5, 10, "Solid line: linear model points 1:3", pos =3)
text(2.5, 9, "Dashed line: linear model points 1:5", pos =3)
plot(Y ~ X, ylab = "Ln(Y)", xlim=c(0,10, main="overall"))
abline(lm(Y[1:3] ~ X[1:3]))
```
[[alternative HTML version deleted]]
______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
You need to mathematically define 'turning point' first: "end of exponential phase" is subjective and meaningless. Once you have a precise mathematical formulation in hand, you can proceed. Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Thu, May 14, 2020 at 8:12 AM Luigi Marongiu <marongiu.luigi at gmail.com> wrote:
Dear all,
I am trying to find a turning point in some data. In the initial phase, the
data increases more or less exponentially (thus it is linear in a nat log
transform), then reaches a plateau. I would like to find the point that
marks the end of the exponential phase.
I understand that the function spline can build a curve; is it possible
with it to find the turning points? I have no idea of how to use spline
though.
Here is a working example.
Thank you
```
Y = c(259, 716, 1404, 2173, 3944, 5403, 7140, 9121,
11220, 13809, 16634, 19869, 23753, 27447,
30590, 33975, 36627, 39600, 42067, 44082,
58190, 63280, 65921, 67929, 69977, 71865,
73614, 74005, 74894, 75717, 76365, 76579,
77087, 77493, 77926, 78253, 78680, 79253,
79455, 79580, 79699, 79838, 79981, 80080,
80124, 80164, 80183, 80207, 80222, 80230,
80241, 80261, 80261, 80277, 80290, 80303,
80337, 80376, 80422, 80461, 80539, 80586,
80653, 80708, 80762, 80807, 80807, 80886,
80922, 80957, 80988, 81007, 81037, 81076,
81108, 81108, 81171, 81213, 81259, 81358,
81466, 81555, 81601, 81647, 81673, 81998,
82025, 82041, 82053, 82064, 82094, 82104,
82110, 82122, 82133, 82136, 82142, 82164,
82168, 82180, 82181, 82184, 82187, 82188,
82190, 82192, 82193, 82194)
Y = log(Y)
X = 1:length(Y)
plot(Y ~ X, ylab = "Ln(Y)", xlim=c(0,10, main="zoomed in"))
abline(lm(Y[1:3] ~ X[1:3]))
abline(lm(Y[1:5] ~ X[1:5]), lty=2)
text(7, 6, "After third or fifth point, there is deviance", pos=3)
text(2.5, 10, "Solid line: linear model points 1:3", pos =3)
text(2.5, 9, "Dashed line: linear model points 1:5", pos =3)
plot(Y ~ X, ylab = "Ln(Y)", xlim=c(0,10, main="overall"))
abline(lm(Y[1:3] ~ X[1:3]))
```
[[alternative HTML version deleted]]
______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
We can use nls2 to try each value in 10:100 as a possible split point picking the one with lowest residual sum of squares: library(nls2) fm <- nls2(Y ~ cbind(1, pmin(X, X0)), start = data.frame(X0 = 10:100), algorithm = "plinear-brute") plot(Y ~ X) lines(fitted(fm) ~ X, col = "red")
fm
Nonlinear regression model
model: Y ~ cbind(1, pmin(X, X0))
data: parent.frame()
X0 .lin1 .lin2
18.0000 6.5570 0.2616
residual sum-of-squares: 4.999
Number of iterations to convergence: 91
Achieved convergence tolerance: NA
On Thu, May 14, 2020 at 11:13 AM Luigi Marongiu
<marongiu.luigi at gmail.com> wrote:
Dear all,
I am trying to find a turning point in some data. In the initial phase, the
data increases more or less exponentially (thus it is linear in a nat log
transform), then reaches a plateau. I would like to find the point that
marks the end of the exponential phase.
I understand that the function spline can build a curve; is it possible
with it to find the turning points? I have no idea of how to use spline
though.
Here is a working example.
Thank you
```
Y = c(259, 716, 1404, 2173, 3944, 5403, 7140, 9121,
11220, 13809, 16634, 19869, 23753, 27447,
30590, 33975, 36627, 39600, 42067, 44082,
58190, 63280, 65921, 67929, 69977, 71865,
73614, 74005, 74894, 75717, 76365, 76579,
77087, 77493, 77926, 78253, 78680, 79253,
79455, 79580, 79699, 79838, 79981, 80080,
80124, 80164, 80183, 80207, 80222, 80230,
80241, 80261, 80261, 80277, 80290, 80303,
80337, 80376, 80422, 80461, 80539, 80586,
80653, 80708, 80762, 80807, 80807, 80886,
80922, 80957, 80988, 81007, 81037, 81076,
81108, 81108, 81171, 81213, 81259, 81358,
81466, 81555, 81601, 81647, 81673, 81998,
82025, 82041, 82053, 82064, 82094, 82104,
82110, 82122, 82133, 82136, 82142, 82164,
82168, 82180, 82181, 82184, 82187, 82188,
82190, 82192, 82193, 82194)
Y = log(Y)
X = 1:length(Y)
plot(Y ~ X, ylab = "Ln(Y)", xlim=c(0,10, main="zoomed in"))
abline(lm(Y[1:3] ~ X[1:3]))
abline(lm(Y[1:5] ~ X[1:5]), lty=2)
text(7, 6, "After third or fifth point, there is deviance", pos=3)
text(2.5, 10, "Solid line: linear model points 1:3", pos =3)
text(2.5, 9, "Dashed line: linear model points 1:5", pos =3)
plot(Y ~ X, ylab = "Ln(Y)", xlim=c(0,10, main="overall"))
abline(lm(Y[1:3] ~ X[1:3]))
```
[[alternative HTML version deleted]]
______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Statistics & Software Consulting GKX Group, GKX Associates Inc. tel: 1-877-GKX-GROUP email: ggrothendieck at gmail.com
Hi Maybe I am wrong but it seems to me that it is cumulative data from recent epidemy in some state. If yes, instead of inventing wheel I would go to canned and proved solution using tools from https://www.repidemicsconsortium.org/ I found useful and enlightening this blog especially first part from February 18th. https://timchurches.github.io/blog/ Cheers Petr
-----Original Message----- From: R-help <r-help-bounces at r-project.org> On Behalf Of Luigi Marongiu Sent: Thursday, May 14, 2020 5:12 PM To: r-help <r-help at r-project.org> Subject: [R] How to find a split point in a curve? Dear all, I am trying to find a turning point in some data. In the initial phase,
the
data increases more or less exponentially (thus it is linear in a nat log
transform), then reaches a plateau. I would like to find the point that
marks the end of the exponential phase.
I understand that the function spline can build a curve; is it possible
with it to find the turning points? I have no idea of how to use spline
though.
Here is a working example.
Thank you
```
Y = c(259, 716, 1404, 2173, 3944, 5403, 7140, 9121,
11220, 13809, 16634, 19869, 23753, 27447,
30590, 33975, 36627, 39600, 42067, 44082,
58190, 63280, 65921, 67929, 69977, 71865,
73614, 74005, 74894, 75717, 76365, 76579,
77087, 77493, 77926, 78253, 78680, 79253,
79455, 79580, 79699, 79838, 79981, 80080,
80124, 80164, 80183, 80207, 80222, 80230,
80241, 80261, 80261, 80277, 80290, 80303,
80337, 80376, 80422, 80461, 80539, 80586,
80653, 80708, 80762, 80807, 80807, 80886,
80922, 80957, 80988, 81007, 81037, 81076,
81108, 81108, 81171, 81213, 81259, 81358,
81466, 81555, 81601, 81647, 81673, 81998,
82025, 82041, 82053, 82064, 82094, 82104,
82110, 82122, 82133, 82136, 82142, 82164,
82168, 82180, 82181, 82184, 82187, 82188,
82190, 82192, 82193, 82194)
Y = log(Y)
X = 1:length(Y)
plot(Y ~ X, ylab = "Ln(Y)", xlim=c(0,10, main="zoomed in"))
abline(lm(Y[1:3] ~ X[1:3]))
abline(lm(Y[1:5] ~ X[1:5]), lty=2)
text(7, 6, "After third or fifth point, there is deviance", pos=3)
text(2.5, 10, "Solid line: linear model points 1:3", pos =3)
text(2.5, 9, "Dashed line: linear model points 1:5", pos =3)
plot(Y ~ X, ylab = "Ln(Y)", xlim=c(0,10, main="overall"))
abline(lm(Y[1:3] ~ X[1:3]))
```
[[alternative HTML version deleted]]
______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting- guide.html and provide commented, minimal, self-contained, reproducible code.